Counterfactuals and Causal Models: Introduction to the Special Issue

Authors

  • Steven A. Sloman

    Corresponding author
    1. Cognitive, Linguistics, & Psychological Sciences, Brown University
    • Correspondence should be sent to Steven Sloman, Cognitive, Linguistic, & Psychological Sciences, Brown University, Box 1821, Providence, RI 02912. E-mail: Steven_Sloman@brown.edu

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Abstract

Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation of something false or nonexistent. Pearl refers to Bayes nets as oracles for intervention, and interventions can tell us what the effect of action will be or what the effect of counterfactual possibilities would be. Counterfactuals turn out to be necessary to understand thought, perception, and language. This selection of papers tells us why, sometimes in ways that support the Bayes net framework and sometimes in ways that challenge it.

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